Batch processing and parallel processing systems have existed for many years. These typically can be used to submit single jobs for processing, for multiple independent jobs, or for a set of related jobs that may comprise sub-steps of a larger job. IBM's LoadLeveler is an example of such a system, and Grid Computing is a new field that builds on what was provided with LoadLeveler, extending it with flexibility and security for use in more diverse environments.
A typical implementation of a parallel processing system allows multiple clients to each submit multiple job steps to be distributed among a pool of clients for processing. This is typically accomplished by having a centralized server receive all such requests, and prioritize and distribute them to a pool of client systems for processing. The centralized server is responsible for workload balancing among the clients, and for the commands to the client systems necessary to start and maintain jobs, and for monitoring activity and notifying the submitter of status, such as completion of the job steps on each client.
In these typical applications, once a job step is initiated on a client system for processing, all communication must flow through the centralized server, and there is little communication with or feedback of results from the job steps to the submitter prior to completion of the job step. This arises from several practical limitations. Due to the fact that the centralized server may be handling many job steps for many submitters simultaneously, and the centralized server is typically a general-purpose server not customized to a specific application, the centralized server does not have the capability or capacity to deal with the particular actions and requirements of each job step on each processing client in real time.